Stock Return Serial Dependence and Out-of-Sample Portfolio Performance
64 Pages Posted: 2 May 2013
There are 2 versions of this paper
Stock Return Serial Dependence and Out-of-Sample Portfolio Performance
Date Written: April 2013
Abstract
We study whether investors can exploit stock return serial dependence to improve out-of- sample portfolio performance. To do this, we first show that a vector-autoregressive (VAR) model estimated with ridge regression captures daily stock return serial dependence in a stable manner. Second, we characterize (analytically and empirically) expected returns of VAR-based arbitrage portfolios, and show that they compare favorably to those of existing arbitrage portfolios. Third, we evaluate the performance of VAR-based investment (positive-cost) portfolios. We show that, subject to a suitable norm constraint, these portfolios outperform the traditional (unconditional) portfolios for transaction costs below 10 basis points.
Keywords: out-of-sample performance, portfolio choice, Serial dependence, vector autoregression
JEL Classification: G11
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Limited Attention, Information Disclosure, and Financial Reporting
-
Investor Psychology in Capital Markets: Evidence and Policy Implications
By Kent D. Daniel, David A. Hirshleifer, ...
-
Market Frictions, Price Delay, and the Cross-Section of Expected Returns
By Kewei Hou and Tobias J. Moskowitz
-
Do Investors Overvalue Firms with Bloated Balance Sheets?
By David A. Hirshleifer, Kewei Hou, ...
-
Why Do New Issues and High-Accrual Firms Underperform: The Role of Analysts' Credulity
By Siew Hong Teoh and T.j. Wong
-
Driven to Distraction: Extraneous Events and Underreaction to Earnings News
By David A. Hirshleifer, Sonya S. Lim, ...
-
Industry Information Diffusion and the Lead-Lag Effect in Stock Returns
By Kewei Hou
-
Learning with Information Capacity Constraints
By Lin Peng